import numpy as np


def sigmoid(x):
    return 1/(1+np.exp(-x))

class Neuron:
    def __init__(self, weights, bias):
        self.weights = weights
        self.bias = bias
    
    def feedforward(self, inputs):
        total = np.dot(self.weights, inputs) + self.bias
        return sigmoid(total)

if __name__ == "__main__":
    weights = np.array([0,1])
    bias = 4
    n = Neuron(weights, bias)

    x = np.array([2,3])
    print(n.feedforward(x))
